Questioning ethics

"Peer review" journals refuse to publish research they call "unethical". This allows ethics-makers to make up ethics to ban research that could disprove their pet theories, avoiding scientific testing. There are many examples of nonsensical assumptions in ethics. For example, bioethicists often talk about risks of unforeseen side effects of genetic engineering, but ignore the fact that "natural" biology has lots of nasty effects like ageing. Since all direction of punishment specifically at individuals capable of conscious decisions would select against that ability, evolution cannot have bequeathed the same species with both an ability of conscious decisions and a sense of that ability being the basis for moral or penal liability. Ergo, the idea of artificial side effects being worse than "natural" ones is a stupid cultural whim that forces people to maligner stupidity at best and dysgenically selects against the capacity for conscious decisions at worst. With that in mind, it would only be good to use genetic engineering to confuse down all legal definitions of "human being". One blatant example of fallacious bioethics "reasoning" is the claim that humans could theoretically interbreed with chimps without genetic engineering but that it would be unethical to test, ignoring the fact that bestiality occurs in all countries so if human/chimp hybrids were possible without genetic engineering we would be finding specimens in the jungle. And yet there are none. Not surprisingly, the ethicidiots frequently cite a conference in 1907, when jungles were barely explored and "we just haven't found them yet" was still plausible (which it isn't anymore).

No association fallacies

To be capable of science is to question theories for what they are, in their own context, not for what they are "generally" associated with. It does not mean that all theories are equal (they certainly are not, some theories are wrong). However, never assume that a certain claim "must" be due to those-and-those motifs, not even if the claim is blatantly wrong. For instance, any evidence that can be denied using conspiracy theories can just as well be denied using cognitive bias theories (or even more easily, since biasing "selfish genes" would just be there, with the same effect as all humans conspiring without even having to technically conspire). It is the untestable denial itself that makes a "theory" unscientific, not any arbitrary distinction between cognitive bias and conspiracy. This is one of many rerasons why those who judge theories by formulation/who published it/that person's status etc are incapable of science. Those who claim "peer review" to be "necessary" protection from pseudoscience and the promoters of real pseudoscience who attack science by lumping it with "peer review" are both equally stupid. Anyone who claims something to be "necessary" to avoid something else and/or assumes that criticism of something "must" come from an agenda promoting something else is incapable of science. Saying as a phrase that a claim must not necessarily come from an agenda but then keeping on as if it did is not one scrap better than flat-out saying that it has to (just like parrots can mimick phrases describing the scientific method without being capable of doing science).

Progressively decreasing Pareto sensitivity

It could theoretically be objected to the principle shown in http://gettingsciencegoingagain.blogspot.se/2015/02/general-new-theories-less-pareto.html that it would have applied to earlier generalizations too, and therefore would obey the Pareto principle. However, that ignores the fact that the path from fine-tuning to generalization is a continuum. While past generalizations like relativity did make more predictions than a fine-tuning, they still make fewer predictions than an even more general theory would. A theory of everything would make the most predictions, thus having the greatest chance of some of them being low-cost testable.

Science and equality

All attempts to counter what is shown in http://gettingsciencegoingagain.blogspot.se/2015/01/non-status-science-is-possible.html that I have received claims that science is about following rules, which is debunked in http://gettingsciencegoingagain.blogspot.se/2015/03/animals-can-follow-rules-so-rules-do.html . It is extremely odd that the same people who claim that "pursuit of status is an important drive for scientists" also claim that "peer review is necessary to prevent cheating caused by pursuit of status". The contradiction shows that only search for objective truth is adequate. This agrees with the fact that status/prestige/authority/credibility thinking is a symptom of a brain too blunt to analyze actual content. This goes regardless if the blunt brain is dominant or submissive, claim to be an authority or believe in others as authorities. Science-capable brains are, thus, neither submissive nor dominant. Science-capable brains analyze the content instead of assessing authority. As it's International Women's Day today, I will debunk gender stereotypes. Gender stereotype-believing psychologists try to explain away the fact that there are science-capable people of both sexes by saying that "the difference within sexes is bigger than that between them", but that is insufficient. If only a small part of a bell curve pokes over an edge, it only takes a small move in the other direction to make sure no part of the curve pokes over the edge. Ergo, the existence of science-capable both men and women falsifies all gender stereotypes both ways. It may seem that the psychological stereotype of women's brains being more complex/plastic than men's is misandrist, but within its own philosophical context (the awful fallacious "belief in plasticity equals social engineering like Stalin and Mao" rhetorics spewed in Steven Pinker's "The blank slate") it is misogynist.

Animals can follow rules, so rules do not define science

It is often claimed that science is defined by formally correct manipulation of (usually mathematical) symbols according to rules, and that thinking about actual content is not relevant. However, there is evidence that animals can manipulate symbols formally correctly without understanding what they mean. Baboons can distinguish correctly spelled words from misspelled ones without understanding their meaning. Keas (a type of parrot from New Zealand) and some relatives of crows can evidently learn formal syntactic structures. Apes and dolphins are known to have learned to use symbols they do not use in the wild. Comparably in a way relevant to math, some human tribes do not use numbers even though they can learn it. So there is no human/animal distinction in formal number manipulation. While animals can only meaningfully count so far, their ability to formally correctly manipulate symbols they do not understand in meaning debunks any relevance of that limitation to formally correct rule following. So if the "follow those rules and you do science" adage was correct, there would have been nonhuman animals doing science. The absence of them shows that science is about that understanding of content that is so phanatically dismissed as irrelevant by academia.

Survival of intellectual curiosity

The whole brain changes allowing scientific objectivity explained in http://gettingsciencegoingagain.blogspot.se/2015/01/non-status-science-is-possible.html also solves the mystery of intellectual curiosity. If intellectual curiosity was a specialized "psychological mechanism" selected by environmental change, it would devolve again during the stable periods between climate changes and never reach a high level. But if the absence of cognition/emotion distinction mean that intelligence itself creates intellectual curiosity, the mystery is solved. By the way, this also solves all sorts of mysteries of behaviors that are evolutionarily disadvantageous: intelligence itself just creates a lot of behaviors without specialized "mechanisms".

General new theories less Pareto-sensitivethan fine-tuning

Some who deny that "peer review" retards science claim that stagnation can be explained by only or mostly economically increased expensiveness, citing the Pareto principle. But the claim that it would be more harsh on breakthrough theories than on fine-tuning of existing ones ignores the fact that more general theories makes a greater number of predictions. Since there is always an individual variation in the cost of experiments, a greater number of predictions means that there is a greater chance of at least one of them being cheaply testable. Fine-tuning of existing theories makes much fewer new predictions. So if the Pareto principle was the culprit behind stagnation, fine-tuning of existing theories would have been more severely stagnated than breakthroughs to more general theories.